{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 2.4 综合案例实战 - 股票数据读取与K线图绘制"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-12-16T06:19:44.555722Z",
     "start_time": "2020-12-16T06:19:37.437367Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 800x575 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import tushare as ts\n",
    "import mplfinance as mpf\n",
    "from pylab import mpl\n",
    "import pandas as pd\n",
    "\n",
    "pro = ts.pro_api('9d674d000f7c730dd3108701a1a1c534bf51bfb03a0ff169a9d11848')  #\n",
    "#https://tushare.pro/user/token\n",
    "df = pro.daily(ts_code='000001.SZ', start_date='20200101', end_date='20201103')\n",
    "\n",
    "#df.sort_values(by='trade_date',ascending=False)\n",
    "#取所有行数据，后面取date列，open列等数据\n",
    "data = df.loc[:, ['trade_date', 'open', 'close', 'high', 'low', 'vol']]\n",
    "data = data.rename(columns={'trade_date': 'Date', 'open': 'Open', 'close': 'Close', 'high': 'High', 'low': 'Low', 'vol': 'Volume'})  #更换列名，为后面函数变量做准备\n",
    "#设置date列为索引，覆盖原来索引,这个时候索引还是 object 类型，就是字符串类型。\n",
    "data.set_index('Date', inplace=True)\n",
    "#将object类型转化成 DateIndex 类型，pd.DatetimeIndex 是把某一列进行转换，同时把该列的数据设置为索引 index。\n",
    "data.index = pd.DatetimeIndex(data.index)\n",
    "\n",
    "#将时间顺序升序，符合时间序列\n",
    "data = data.sort_index(ascending=True)\n",
    "\n",
    "#pd.set_option()就是pycharm输出控制显示的设置\n",
    "pd.set_option('expand_frame_repr', False)#True就是可以换行显示。设置成False的时候不允许换行\n",
    "pd.set_option('display.max_columns', None)# 显示所有列\n",
    "#pd.set_option('display.max_rows', None)# 显示所有行\n",
    "pd.set_option('colheader_justify', 'centre')# 显示居中\n",
    "\n",
    "\n",
    "mpl.rcParams['font.sans-serif'] = ['SimHei']  # 指定默认字体\n",
    "mpl.rcParams[\"figure.figsize\"] = [6.4, 4.8]\n",
    "mpl.rcParams['axes.unicode_minus'] = False  # 解决保存图像是负号'-'显示为方块的问题\n",
    "\n",
    "mpf.plot(data, type='candle', mav=(5, 10, 20), volume=True, show_nontrading=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 下面代码废弃了"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 2.4.1 初步尝试 - 股票数据读取与可视化"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "1.股票数据库：Tushare库的安装与使用"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "首先推荐通过PIP安装法来安装可以调用股价数据的Tushare库（Tushare库官方地址为：http://tushare.org/\n",
    "以Windows系统为例，具体方法是：通过Win + R组合键调出运行框，输入cmd后回车，然后在弹出框中输入pip install tushare后按一下Enter回车键的方法来进行安装。如果在1.2.3节讲到的Jupyter Notebook编辑器中安装的话，只需要在代码框中输入如下代码然后运行该行代码框即可（注意是英文格式下的!）：\n",
    "!pip install tushare"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>date</th>\n",
       "      <th>open</th>\n",
       "      <th>close</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>volume</th>\n",
       "      <th>code</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2009-01-05</td>\n",
       "      <td>5.086</td>\n",
       "      <td>5.178</td>\n",
       "      <td>5.178</td>\n",
       "      <td>5.008</td>\n",
       "      <td>936048.88</td>\n",
       "      <td>000002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2009-01-06</td>\n",
       "      <td>5.163</td>\n",
       "      <td>5.333</td>\n",
       "      <td>5.372</td>\n",
       "      <td>5.109</td>\n",
       "      <td>1216831.18</td>\n",
       "      <td>000002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2009-01-07</td>\n",
       "      <td>5.356</td>\n",
       "      <td>5.302</td>\n",
       "      <td>5.457</td>\n",
       "      <td>5.302</td>\n",
       "      <td>834829.31</td>\n",
       "      <td>000002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2009-01-08</td>\n",
       "      <td>5.217</td>\n",
       "      <td>5.333</td>\n",
       "      <td>5.410</td>\n",
       "      <td>5.163</td>\n",
       "      <td>837661.70</td>\n",
       "      <td>000002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2009-01-09</td>\n",
       "      <td>5.333</td>\n",
       "      <td>5.325</td>\n",
       "      <td>5.418</td>\n",
       "      <td>5.263</td>\n",
       "      <td>626815.66</td>\n",
       "      <td>000002</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         date   open  close   high    low      volume    code\n",
       "0  2009-01-05  5.086  5.178  5.178  5.008   936048.88  000002\n",
       "1  2009-01-06  5.163  5.333  5.372  5.109  1216831.18  000002\n",
       "2  2009-01-07  5.356  5.302  5.457  5.302   834829.31  000002\n",
       "3  2009-01-08  5.217  5.333  5.410  5.163   837661.70  000002\n",
       "4  2009-01-09  5.333  5.325  5.418  5.263   626815.66  000002"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 我们只需要通过如下2行代码便可获取到股票基本数据：\n",
    "import tushare as ts\n",
    "df = ts.get_k_data('000002', start='2009-01-01', end='2019-01-01')\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 此时如果想要将股票数据获取到Excel文件中，则可以使用2.2.2节相关知识点，代码如下：\n",
    "df.to_excel('股价数据.xlsx', index=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "2.绘制股价走势图"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "已经有了股价数据后，我们可以通过可视化的方式将其展示出来，这里我们首先利用2.2.1节的补充知识点中的set_index()函数将日期设置为行索引，这样方便等会直接用pandas库进行绘图，代码如下："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>open</th>\n",
       "      <th>close</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>volume</th>\n",
       "      <th>code</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2009-01-05</th>\n",
       "      <td>5.086</td>\n",
       "      <td>5.178</td>\n",
       "      <td>5.178</td>\n",
       "      <td>5.008</td>\n",
       "      <td>936048.88</td>\n",
       "      <td>000002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-01-06</th>\n",
       "      <td>5.163</td>\n",
       "      <td>5.333</td>\n",
       "      <td>5.372</td>\n",
       "      <td>5.109</td>\n",
       "      <td>1216831.18</td>\n",
       "      <td>000002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-01-07</th>\n",
       "      <td>5.356</td>\n",
       "      <td>5.302</td>\n",
       "      <td>5.457</td>\n",
       "      <td>5.302</td>\n",
       "      <td>834829.31</td>\n",
       "      <td>000002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-01-08</th>\n",
       "      <td>5.217</td>\n",
       "      <td>5.333</td>\n",
       "      <td>5.410</td>\n",
       "      <td>5.163</td>\n",
       "      <td>837661.70</td>\n",
       "      <td>000002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-01-09</th>\n",
       "      <td>5.333</td>\n",
       "      <td>5.325</td>\n",
       "      <td>5.418</td>\n",
       "      <td>5.263</td>\n",
       "      <td>626815.66</td>\n",
       "      <td>000002</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             open  close   high    low      volume    code\n",
       "date                                                      \n",
       "2009-01-05  5.086  5.178  5.178  5.008   936048.88  000002\n",
       "2009-01-06  5.163  5.333  5.372  5.109  1216831.18  000002\n",
       "2009-01-07  5.356  5.302  5.457  5.302   834829.31  000002\n",
       "2009-01-08  5.217  5.333  5.410  5.163   837661.70  000002\n",
       "2009-01-09  5.333  5.325  5.418  5.263   626815.66  000002"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.set_index('date', inplace=True)\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "通过2.3.1节补充知识点中pandas绘图的相关知识点来进行图形绘制，代码如下。因为在pandas库中plot()函数默认绘制的是折线图，所以直接写plot()即可，不需要传入kind参数。此外在金融领域，通常用收盘价作为当天价格来绘制股价走势图，因此这里选择的是close这一列。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x2077b28e1d0>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['close'].plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "如果想给图片加一个标题，在pandas库中使用可以在plot()可以在里面传入一个title参数，代码如下，注意因为标题是中文内容，所以要写2.3.2节最后讲到的两行代码防止中文乱码。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x2077d76bbe0>"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "plt.rcParams['font.sans-serif'] = ['SimHei']  # 用来正常显示中文标签\n",
    "df['close'].plot(title='万科股价走势图')    "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**补充知识点：直接使用Matplotlib库画图的注意点**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "上面使用的是pandas库中的plot()函数，pandas库其实是集成了Matplotlib库的一些功能，如果有的读者想直接用Matplotlib库进行股价走势画图，可以采用如下代码："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 通过Tushare库获取股价数据\n",
    "import tushare as ts\n",
    "df = ts.get_k_data('000002', start='2009-01-01', end='2019-01-01')\n",
    "\n",
    "# 要注意的细节：调整日期格式使得横坐标显示清晰\n",
    "from datetime import datetime\n",
    "df['date'] = df['date'].apply(lambda x:datetime.strptime(x,'%Y-%m-%d'))\n",
    "\n",
    "# 绘制折线图\n",
    "import matplotlib.pyplot as plt\n",
    "plt.plot(df['date'], df['close'])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 2.4.2 综合实战 - 股票K线图绘制"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**1.股票K线图基本知识**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "一个实际中的股票K线图如下图所示（这个是“贵州茅台”股票的日线级别的K线图）：\n",
    "![图片解释](https://uploader.shimo.im/f/wiLdVEhqGd4KndWk.png)\n",
    "\n",
    "没有接触过股票的读者可能会被里面的各个柱状图和折线图搞得一头雾水，而这些图形其实都是通过一些很基础的数据绘制而成，这一节便主要来科普下股票K线图的基本知识。\n",
    "这些柱状图，通常称之为“K线图”，是由股票的四个价格来绘制的：开盘价（当天上午9点半开始交易时的价格）、收盘价（当天下午3点结束交易时的价格）、最高价（当天股价波动中的最高价）、最低价（当天股价波动中的最低价），简称“高、开、低、收”四个价格。\n",
    "如下图所示，根据这四个价格便可以绘制出红色和绿色的K线图，因为形似蜡烛，因此也常被称之为蜡烛图。K线图分为两种，如果当天的收盘价高于开盘价，也就是说当天的价格上涨，则称之为阳线，通常绘制成红色；反之如果当天的收盘价低于开盘价，也就是说当天的价格下跌，则称之为阴线，通常绘制成绿色。补充说一句，在美国，反而是红色代表跌，绿色代表涨。\n",
    "\n",
    "![图片解释](https://uploader.shimo.im/f/blJRkjs9ejABHFgE.png!thumbnail)\n",
    "        \n",
    "这里再解释下均线图，也就是那些折线图的绘制原理。均线分为5日均线（通常称之为MA5）、10日均线（通常称之为MA10）、20日均线（通常称之为MA20）等，其原理就是将股价的收盘价求均值，例如5日均线就是最近连续5个交易日收盘价之和的平均值，具体的计算公式如下，其中Close1为当天的收盘价，Close2为前一天的收盘价，其余依次类推。\n",
    "MA5 = (Close1 + Close2 + Close3 + Close4 + Close5)/5\n",
    "\n",
    "把每个5日均线的值连成一条平滑的曲线就是5日均线图了，同理10日均线图和20日均线图也是类似的原理，这些均线图也就是我们在这一小节最开始看到图中的那些折线图。\n",
    "了解了股票K线图的基本知识后，下面我们就来进行K线图的绘制工作。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**2.绘制股票K线图**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "(1) 安装绘制K线图的相关库：mpl_finance库"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "首先需要安装绘制K线图的相关库：mpl_finance库，其安装办法稍微麻烦一点，推荐通过PIP安装法安装，以Windows系统为例，具体方法是：通过Win + R组合键调出运行框，输入cmd后回车，然后在弹出框中输入如下内容，按一下Enter回车键进行安装：\n",
    "\n",
    "pip install https://github.com/matplotlib/mpl_finance/archive/master.zip"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "如果是在在1.2.3节讲到的Jupyter Notebook中安装，则在pip前面加一个英文的感叹号“!”然后运行该代码块即可。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 通过如下代码，可以在Jupyter Notebook中安装。（需取消注释）\n",
    "# !pip install https://github.com/matplotlib/mpl_finance/archive/master.zip"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "(2) 引入绘图相关库"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 首先引入一些绘图需要用到的库，代码如下：\n",
    "import tushare as ts\n",
    "import matplotlib.pyplot as plt\n",
    "import mpl_finance as mpf\n",
    "import seaborn as sns\n",
    "sns.set()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "第一个引入2.4.1节讲到的Tushare库，第二引入2.3.1节讲到的Matplotlib库在；第三个引入刚刚安装的mpl_finance库；第四个seaborn库是一个图表美化库，通过sns.set()即可激活，如果是通过1.2.1节Anaconda安装的Python，那么就自带该库了，无需额外安装。上面的代码直接拿去运行即可。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "(3) 通过Tushare库获取股票基本数据"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>date</th>\n",
       "      <th>open</th>\n",
       "      <th>close</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>volume</th>\n",
       "      <th>code</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>99</th>\n",
       "      <td>2019-06-03</td>\n",
       "      <td>26.81</td>\n",
       "      <td>26.44</td>\n",
       "      <td>27.02</td>\n",
       "      <td>26.28</td>\n",
       "      <td>317567.0</td>\n",
       "      <td>000002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>100</th>\n",
       "      <td>2019-06-04</td>\n",
       "      <td>26.47</td>\n",
       "      <td>26.30</td>\n",
       "      <td>26.54</td>\n",
       "      <td>26.25</td>\n",
       "      <td>203260.0</td>\n",
       "      <td>000002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101</th>\n",
       "      <td>2019-06-05</td>\n",
       "      <td>26.64</td>\n",
       "      <td>27.03</td>\n",
       "      <td>27.28</td>\n",
       "      <td>26.63</td>\n",
       "      <td>576164.0</td>\n",
       "      <td>000002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>102</th>\n",
       "      <td>2019-06-06</td>\n",
       "      <td>27.01</td>\n",
       "      <td>27.12</td>\n",
       "      <td>27.29</td>\n",
       "      <td>26.92</td>\n",
       "      <td>333792.0</td>\n",
       "      <td>000002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>103</th>\n",
       "      <td>2019-06-10</td>\n",
       "      <td>27.29</td>\n",
       "      <td>27.81</td>\n",
       "      <td>28.05</td>\n",
       "      <td>27.17</td>\n",
       "      <td>527547.0</td>\n",
       "      <td>000002</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           date   open  close   high    low    volume    code\n",
       "99   2019-06-03  26.81  26.44  27.02  26.28  317567.0  000002\n",
       "100  2019-06-04  26.47  26.30  26.54  26.25  203260.0  000002\n",
       "101  2019-06-05  26.64  27.03  27.28  26.63  576164.0  000002\n",
       "102  2019-06-06  27.01  27.12  27.29  26.92  333792.0  000002\n",
       "103  2019-06-10  27.29  27.81  28.05  27.17  527547.0  000002"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 通过Tushare库获取股票代码为“000002”的股票“万科A”在2019-06-01至2019-09-30的股价数据，代码如下：\n",
    "df = ts.get_k_data('000002','2019-06-01', '2019-09-30')\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "(4) 日期格式调整及表格转换"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "因为绘制K线图的candlestick_ochl()函数只能接收特定格式的日期格式，以及数组格式的内容，所以我们需要将原来文本类型的日期格式调整一下，代码如下：\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[737213.0, 26.81, 26.44, 27.02, 26.28, 317567.0, '000002'],\n",
       "       [737214.0, 26.47, 26.3, 26.54, 26.25, 203260.0, '000002'],\n",
       "       [737215.0, 26.64, 27.03, 27.28, 26.63, 576164.0, '000002'],\n",
       "       [737216.0, 27.01, 27.12, 27.29, 26.92, 333792.0, '000002'],\n",
       "       [737220.0, 27.29, 27.81, 28.05, 27.17, 527547.0, '000002']],\n",
       "      dtype=object)"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 导入日期格式调整涉及的两个库\n",
    "from matplotlib.pylab import date2num\n",
    "import datetime\n",
    "\n",
    "# 对tushare获取到的日期数据转换成candlestick_ohlc()函数可读取的数字格式\n",
    "def date_to_num(dates):\n",
    "    num_time = []\n",
    "    for date in dates:\n",
    "        date_time = datetime.datetime.strptime(date,'%Y-%m-%d')\n",
    "        num_date = date2num(date_time)\n",
    "        num_time.append(num_date)\n",
    "    return num_time\n",
    "\n",
    "# 将DataFrame转换为二维数组，并利用date_to_num()函数转换日期\n",
    "df_arr = df.values  # 将DataFrame格式的数据，转换为array二维数组\n",
    "df_arr[:,0] = date_to_num(df_arr[:,0])  # 将原来日期格式的日期换成数字格式\n",
    "\n",
    "df_arr[0:5] # 查看此时的df_arr的前5项"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "(5) 绘制K线图"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "转换好数据格式后，K线图的绘制就比较简单了，通过candlestick_ochl()函数便能够轻松的绘制K线图了，代码如下："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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1denUqVP6yU9+ogULFqQvagAAAADwqYQjaZs2bVJPT48qKioity1evFjLly/XrbfeqjNnzuimm25SUVGRpYECAAAAgB8kTNLKy8tVXl4e876vfe1raQ8IgPW69tZT1h4AAMBQCac7AvCe7qYmp0NIiyl5FzsdAgAAQNqRpAFwrRnBq50OAQAAIO2SLsEPwP0aVpaot6NDkvTx668pf32lwxEBAABgMEbSAB/pT9AG/x8AAADmIEkDAAAAAIOQpAEAAACAQUjSAAAAAMAgJGkAAAAAYBCSNACAJ+Tl5A55vKf5HTvDAQBg2CjBDwDwhIp5qyVJ2957VaHLC8+5v/GjZl02Od/usAAASBkjaQCUFQgMeQwAAAD7MJIGILKpdVt1lSYWL3I4GgAAAH9jJA3wqPa3fu10CAAAABgGkjTAo0683+h0CCmbknex0yEAAAA4jiQNgDFmBK92OgQAAADHsSYN8JiGlSXq7eg4e/AfLykrEIisOUtkzLRpFkYGAACAZDCSBnhMJEGLczyU3FnXpjscAAAApIgkDQAAAAAMQpIGAAAAAAYhSQMAAAAAg5CkwdP2tR5wOgQANmMrBwCA21HdEZ7W3NlCWfcoWYFApJBIViDgcDSANQa/58vq1qjzVJck6eWD25SXk6uKeaudCA0AgKSQpAE+0l+Kv626ShOLFzkcDWCP/gQt3jEAAKYhSfO4rr31ni2rPmA/MCml/cAAAAAAU7EmzeO6m5qcDsEyI9kPDAAAADAVSRoAwNPycnKHPAYAwDRMd4QnRRcK+O+WtygSAPhY//v/taOv64bJBQ5HAwBAYoykwTVSKacfXRiAIgEAAABwE5I0uEZzZ4vTIQAAAACWY7qjR0VXPjxeU03lQwAAAMAlGEnzKL9XPowuDECRAAAAALgJI2k+ta/1gGYEr7b8OU7pLxSw7b1XFbq80OFoAAAAgOQxkuZTw1nfxZow7xgzbZrTIQAAACAOkjQgSV1762PenkrVSVPkzrrW6RAAo8R7fwMA4ASmO/pM9P5h2xt3Ki8nlz3EktTd1BQzuWnubHHNNFAAscV7fwMA4ARG0nxm8J5h7CEGAAAAmIWRNDiia2990t9aM/oHIB0uHTfF6RAAAEgKSRockcrUIlNH/0xNHrMCgQFbLmQFAg5GA5hj9pSZam3tdDoMAAASIkkDhsnU5LF/0/KTO7frvC8vcDgaAAAApIo1aQAAAABgEEbS4GlT8i4e8Wu0VVfpeE21JOl4TbUuLCrWxOJFI35dAAAAIBaSNBhlX+uBtJazT8drTSxepInFi9RWXUVyBgAAAMsllaRt3LhRtbW1kqSCggKVlpaqrq5Oa9euVV9fn6666ir9wz/8g3JyciwNFt4WXYjDlCIcVkl3MgoAAADvSLgmbffu3aqrq1NVVZW2bNmigwcP6pe//KUeeeQRbdiwQVu3blV3d7eqq6vtiBceFl14w5QiHFZp7mxxOgQAAAAYKmGSFgwGVVZWppycHI0aNUr5+flqaWlRb2+vurq61Nvbq56eHo0ePdqOeBFH1976tL3WvtYDaXstAAAAAKlJON1x+vTpkf83NjaqtrZWL7zwgv7sz/5Md9xxh3JzczVlyhTNnz/f0kAxtFT2HUukubOFqXgxjJk2zekQAAAA4ANJFw45fPiwli1bptLSUp1//vlat26dtm7dqilTpujxxx/X448/rkcffTTpE0+YkDusgIcjGMyz7VxOOXn+6AE/56EYjwkG83TBmIA+7v7TRscXjAlEnre0+qHIfdsbd+qCMQE9V/xE3NsHv/ZI4o1lqPuDwby4P6NVgoVfSvyYJM8/9mjin3+k2i+7VBN8cO07zQ+/X7xkcH/tuetenf7oI0lnq7eOGjdOs/99kxOheQbvCfehz6xHG5vH9D5JKkmrr69XSUmJVq1apVAopNraWn3605/WtP8fWfj617+uv/mbv0npxO3tXerrC6cecYqCwTy1tnZafh6nnTjRk/DnbG3t1Pe/UC5J2vbeqwpdXhi5XdKA5K3/uLW1M+7t/YbTxsnGm+p9Tvd19PmHKg7ySRI//0gFPz/H8fbwOr/8fvGKWP3Vn6BFH9Onw8d7wn3oM+vRxuYxoU8yMzOGHLRKuCbtyJEjWr58udatW6dQKCRJ+vSnP639+/erra1NkrRr1y597nOfS1PIgDcMpzgI6wEBAACQcCRt06ZN6unpUUVFReS2xYsX64EHHtCdd96prKwsXXLJJVqzZo2lgQJ+wHpAAAAAJEzSysvLVV5eHvO+RYvY2NcP8nJyB5TEz8uxbz0hAAAA4DdJFw6Bf/VvKh29jm24GlaWqLfj7Bq34zXVygoElL++csQxAgAAAF5BkgZb9Sdo8Y7dZDgjjGV1ayLP2d64U3k5uZEkGACc0LW3Pm1buAAA0oMkzaOyAoEBCVBWIOBgNN40nBHG6KQu+pjkDYBT0rnPJgAgPUjSPKp/CiHfkNpvqIQr3uhbvOQNAKJF/36RxBc6AOBRJGkel0qCRoGQ9Bgq4Urn+j4A/sMXOgDgDyRpLhddiOPj119LugjHlLyLz7nNjgSCaZixkSADiIXZEIAzeO/BaSRpLhed8KRShGM4e3HFSuxS1Z9EtlVXaWKxN7dwGE7CxQgbgFhYLwbYK/rLb0lUoYZjSNKQNDZZTg4JF+Bv+1oPuOL3pd+2RHFLv8BZdlShZm0pkpHpdADwpzHTpjkdAgCcM+U6HVOwmztbRvwadkjmw+i+1gMxnxvvdpO5pV/gfawtRTIYSYMjKGgCwATpnILtxa00mjtbYo4+xbsdAJAeJGkwRnQyFp2IxZs+aHoRkqHW8KVjfR8As/DtOAAgXUjSYIyKeatTWsdlehGSob5ljncfyRvgDKZgJ8eLo4UAYCLWpAEGYfoQ4AwqKCaH0UIAsAcjaQAAGMZvlRcBAAORpMH1nJ6mxBRFAOlmRxnwoTCtEQCcxXRHuJ7T05SYogjAa5jWCADOIknDOUwdGTI1LgAAACCdSNJwDlNHhkyNCwBGqmtvvdMhAAAMwpo0AAAc1t3U5PjUbb+JXncniXV3AIzCSBoAAIbJCgSGPMbIse4OgMkYSQMAwDD95fbbqqs0sXiRw9EAAOzGSBoAAAAAGIQkDQAAAAAMQpIGAAAAAAYhSQMAAAAAg1A4BAAAeFZ0qf3tjTsptQ/AFRhJg1Gm5F3sdAgAAACAoxhJg1FmBK92OgQAgIf0j5pte+9VhS4vdDgaAEgOI2kAADikYWWJDi25W8drqtWwsuSc+8dMm+ZAVO7Vtbfe6RAQw77WA7ach/6Hl5CkAQBgg1gfIHs7OmL+v1/urGstjSmevJzcIY9N1d3U5HQIiKG5s8WW86Ta/3Ylj8BwMN0RAAAbdDc1OZZ0xZIVCAxIDLMCgcj/mSIIP2jubGGZBYxFkmaxrr31lv5Rjv4jG/0HFgDgPXk5uZFKhf3Hw5W/vlKS1FZdpYnFi0YcG+AWVPyEG5CkpUm8ZMzqb075IwsA/mHFCBfr3mLb13qAURaPGPwZLfqLjljHgAlI0tLEtGksAAAkwy9/u5Ld4iV6lEUSoywewGc0uBFJGgAA8LxkR8UYZfGOhpUlkSUhx2uqlRUIRGYgAaajuiMAAAA8Z3DF1FgVVJ0wkuqpbDPgH4ykAQAAwHOGqmDqpJGsLWXqpn+QpHkEC78BAOmW7DoupzGtDbFQXA1uRpLmEXyrAgDuM9xtVOxKntxS3XA409rSuZ0BMByx3sfRhWsoWuNvJGkAADhkuN/0O5U8eSmxYcNuxGLnFMlY7+Po9xdFa/yNJM0iTL0AAHiNFxMbt0zphD34rAZTUN3RIqZWFAIAAH/ilimdAPwlqZG0jRs3qra2VpJUUFCgOXPmaP369ZH7jx49qhkzZuiZZ56xJkoAAAAghujZSx+//povR8P2tR7gCwePSZik7d69W3V1daqqqlJGRoaWLFmiWbNmqbq6WpLU2tqq2267TQ8//LDlwQIA4EVU6AUwHNGFRiSKjXhJwiQtGAyqrKxMOTk5kqT8/Hy1tLRE7l+7dq0WL16sSy+91LIgTcbaMwDASFGhFxg+P5faH1xchGIj3pEwSZs+fXrk/42NjaqtrdULL7wQOd6zZ48ee+wx6yJ0QCpDxvHWnpm6gSIAwBrxKh/yZR5gD0ak4SVJV3c8fPiwli1bptLS0sio2YsvvqhvfOMbkVG2VEyYYF/Z3mAwL6XHHz/anvRzDsU5X3Dz85Kkphde1LTbbk3p/G6UahvDHvSL9Whjd7GyvzYtelKStKf5Hc2eMjNy+6EYX+a5/boZe3R03J/BiZ8t3t/idHF7fyVi9c831PWSTsHCL8W8/eT5ic9vdXzDff3BzzPhZ/EK09spqSStvr5eJSUlWrVqlUKhUOT2Xbt2adOmTcM6cXt7l/r6wsN6biqCwTy1tnam9JxPTvSk/Jxo0c89McLXcoPhtDGsR79YjzZ2F7v667LR+QnP4/brJt7fSZPeE+mMw8qfyemCD3b02Ug/V41U74TJjr4nR9LGg5+XzOdKU96DJjPhd1VmZsaQg1YJS/AfOXJEy5cv17p16wYkaMePH1d3d7emTp2ankgBAACSsK/1gGWvPXiDbqs37G7ubEn8IIyIn9d8WvlegbUSjqRt2rRJPT09qqioiNy2ePFiffazn9WnPvUpS4MDAAAYrLmzxbLRJy9u2A33G+7aVivfK7BWwiStvLxc5eXlMe976aWX0h6Q17CIFQAA4Fxde+sdGeWKV+THZPEK1cG7ki4cguHx8xA7AMCbpuRd7Mh5o/eE2t6409I9oZz6Gf0iemTI7oqnfhkt7X+/WP1egTUSrkkDAACI5ofpU374GeFt0aOF7J/mPoykAQAAV/DLCIgf5K+v9OXm00CyGEkDAAAAAIMwkgYAAIC0s3MNoVdEFzWJLmiSFQgMKBaSFQjYHhvsRZIWhV8mAAAA6TF4HRTrohKrmLc65nTe/sIqqUwRjZfwwR1I0qLwywQAAPdhlAF+kcrWTvESPrgDSRoAAHC14YwyAG7cZoGtnfyDwiEAAAAYsa699U6HkBK2WYDJSNIAAAAwYt1NTU6H4DuD15qx9sw7mO4IAAA8IZX1OkifhpUlkTWBx2uqlRUIKH995YDCFRIJhBXYO9C7SNIAAIAneGm9Ttfeetf8PNFFW6KPSSCGx41r5ZB+THcEAAAwDFMH/Yu1cpBI0kZscJlfyv4CAKLxdwLptq/1gNMhpCTeyBDTU4H4mO44Qv1lf900LQEAYB/KwyOWsro1kfVa2xt3Ki8nNzI9MJHmzhZXjbbEi5XPTdZj6qR7MZKWJvyiAQAAyYouqBHrGEhFvGTMTck8BmIkDQAAwAWiR9/+u+WtpEfe4H0kY97DSBoAAICF0rWGLHq0jZE3wNtI0lLgtoW6AADAec2dLUk/tq26SoeW3K3jNdU6tORutVVXWRgZAFMx3TEFbluoCwCAKfa1HuBvaJR4Gz1PLF6kicWLKDQD+BxJGgAAsBxfdA7ERs8AhkKSBgAAACCu6KI1qWwXgeEjSUvCSPYyAQAA/tX/GSLe5wf2sYIbULTGfhQOidI/H3zwMXuZAAAAKzAFFEAsjKRFYX44AADD1/7Wr6X8qyw/j5tGnyrmreZzBYCUkaQBAGCDMdOmOR2C5U6836jzBiVpViwZYPQJcL+uvfXKnXWt02EYi+mOAADYwK8fRlgyACCW7qYmp0MwGkkaAACAYfww8gogPqY7AgCAEWtYWaLejg7pP15SViCg/PWVTofkan4deQVwFiNpAABgxHo7OmL+H4D37Ws94HQInkOSloR4pfkBAAAAv2vubHE6BM9humMMg0v7UpofAIDhycvJHVAshC86ASAxkrQYKO0LAEB68EUnAKSOJC0Fbto8EwAAALBSon0Q97UeYPBjmFiTlgIuMgAAAOCsRPsgslZt+BhJAwAAcLHo0QxJ54xmACaJbNch6XhNdWTLDq7jgRhJAwAAsJDVyyUSjWYAJhm8RUf/MdfxQCRpAAAAFmK5BIBUkaQBAADLUXwLcK/orTPYRsMerEkDAACWYzQJcK94W2mYvg+im6tLkqQBAAAASJnp+yA2d7aQpAEAAADwn8HTmYfaPy0rEFwPne0AAA7lSURBVBhQPCQrELAvUBdJKknbuHGjamtrJUkFBQUqLS3V3r179fjjj+vEiRP6zGc+o4qKCuXk5FgaLAAAAACzDB6tGqpSY/76SklSW3WVJhYvsj44l0pYOGT37t2qq6tTVVWVtmzZooMHD6qqqkorVqzQmjVrtG3bNknSyy+/bHmwAAAAsF7X3vqYt+9rPWBzJIA/JUzSgsGgysrKlJOTo1GjRik/P18ffPCBZs6cqSuuuEKSVF5err/4i7+wPFgAAABYr7upKebtzZ0tNkcC+FPCJG369OmaOXOmJKmxsVG1tbXKycnR2LFj9eCDD6q4uFhPP/20AswnBQAAAHxvcJXHWFUfx0ybZlc4rpR04ZDDhw9r2bJlKi0t1R//+EfV1dXpxRdf1MUXX6xHHnlEzz77rFasWJH0iSdMsK9EZzCYZ9u5/Io2NhP9Yj3a2F3oL+u8P26cTn/0kSRp1LhxtLUNhmrjVNo/1mNPnj865u1jj557+6ERnt8PvNIeV/XkJ/WzbFr0pCTppQNb9fWrb4r5mGDhlwYcXzAmoI+7OwYcj7TdYl2vkfMb3idJJWn19fUqKSnRqlWrFAqF9LOf/UwzZszQ1KlTJUk33nijfvKTn6R04vb2LvX1hVOPOEXBYJ5aWzstP4+f0cZmol+sRxu7C/1lrcvWPaWTO7frvC8vkCTa2gLRe1Ll5eQO2cbJtn+898WJEz0Dbo+u1vfywW0DqvWN5Px+4KXfPZeNzk/pZ/lk0HU0lO9/oVzSwHL+w223RNerCX2SmZkx5KBVwiTtyJEjWr58uTZs2KC5c+dKkubNm6enn35aR44c0UUXXaTXXntNn/3sZ9MXNQAAAAZwck+qoar1AabxwvWaMEnbtGmTenp6VFFREblt8eLFWrNmje6//3719PToyiuv1EMPPWRpoAAAAADcY/D+aUhewiStvLxc5eXlMe/70pe+lO54AAAAAHjA4P3TkkFid1bShUMAAADgbQ0rS9TbcbZ4w/GaamUFApHNhwE7DCexGyx6/Wb/sduQpAEAAECSIglavGPADZxcv5kuCfdJAwAAgDmYDgZ4H0kaAACAi6RjOlg6ZQUCQx4DSB3THQEAADBs/WvW2qqrNLF4kcPRAH/i5lFnRtIAAABcbHBRBDcWSQCsYNqocyoYSQMAAHAxLxRJADAQI2kAAACQxPoywBSMpAEAAEDSyNaXjZk2zYqQAF9iJA0AAAAjljvrWqdDADyDJA0AAAADDB4VozgJYC+mOwIAAHhAOsuNDx4VozgJYC9G0gAAQFqcf9mlTofga24uNw5gIJI0AACQFhM+P8fpEADAE0jSAAAAkJR0TqkEEB9JGgAAAJLClErAHiRpAAAAAGAQkjQAAAAAMAhJGgAAAAAYhCQNAAAAAAxCkgYAAAAABiFJAwAAAACDkKQBAAAAgEFI0gAAAADAICRpAAAAAGAQkjQAAAAAMAhJGgAAAAAYhCQNAAAAAAyS7dSJMzMzPHkuv6KNzUS/WI82dhf6y3q0sfvQZ9ajjc3jdJ8kOn9GOBwO2xQLAAAAACABpjsCAAAAgEFI0gAAAADAICRpAAAAAGAQkjQAAAAAMAhJGgAAAAAYhCQNAAAAAAxCkgYAAAAABiFJAwAAAACDkKQBAAAAgEEcSdI2btyoUCikUCiktWvXSpJ2796toqIiFRYWasOGDec8p7S0VL/4xS8ix/v379ctt9yioqIiLVu2TK2trTHP1dLSottvv13z58/Xt771LZ04cUKS1NXVpW9/+9tauHChFi5cqIMHD6b0/H4/+9nPVFZWNqx2sJKb2rjfU089paeffjpyvGfPHs2ZM0fFxcUqLi7Www8/nHI7mMaEfvnLv/zLSJt+5Stf0VVXXaW2trakn9+Pa3/kbdzPD9d+PCb018cff6ylS5fq5ptv1le/+lX99re/jfn8jo4O3Xfffbrxxht1++23n3OeN954Q3fdddew2sFKbmrjfoN/v3zwwQeaNWtW5D1x7733ptwObmJCnzU2Nuqb3/ymioqKdMcdd+j999+P+XzeF9a3cT+vvy/s7JN+g//+Jrqe+9nyGSlsszfeeCN86623hnt6esKnTp0K33nnneGamppwQUFBuKmpKXz69OnwPffcE/7Vr34VDofD4T/+8Y/hZcuWha+55prwz3/+83A4HA739fWFCwoKwm+++WY4HA6Ht23bFl62bFnM8913333hrVu3hsPhcHjjxo3htWvXhsPhcHjVqlXhJ598MhwOh8Ovv/56+Ktf/WpKz+/u7g4/+eST4ZkzZ4YfeuihdDRN2ritjTs6OsIPP/xw+JprrglXVlZGbt+0aVP4n//5n9PQImYwpV+ifec73wn/6Ec/Sun5XPt/MtI29su1H48p/bVhw4bI/3ft2hVevHhxzOf//d//ffiZZ54Jh8PhcFVVVfiBBx4Ih8PhcG9vb3jTpk3h2bNnh7/5zW+mo2nSxm1tHO/3y44dO8Lf/e5309Ai5jOlzxYvXhx5vb1794ZvvvnmmM/nfWF9G/vhfWF3n8T7+xvveh7Mjs9Ito+kBYNBlZWVKScnR6NGjVJ+fr4aGxt1ySWXaOrUqcrOzlZRUZF27NghSaqpqdGf//mf68Ybb4y8xocffqju7m59/vOflyTdcMMNqqur06lTpwac6/Tp03r77bf1la98RdLZb7d37NihcDisV199Vffdd58k6frrr9f3v//9c2KN93xJevvtt9XX16fvfOc7aW6hkXNTG0vSrl27dOmll+qv/uqvBtz+7rvvqq6uTkVFRbr//vt15MiR9DSQQ0zol2hvvvmm/ud//kdLly49J1aufevbWPLPtR+PKf3V19cX+Rb05MmTGjNmTMx4f/WrX6moqEiSdNNNN+m//uu/dPr0aTU0NKihoUHf+9730tg66eG2No73++Xdd9/VoUOHVFxcrDvvvFO/+93v0tA6ZjKlz377299q/vz5kqSZM2fq2LFj+sMf/nBOvLwvrG9jP7wv7OwTKf7f33jXczS7PiPZnqRNnz5dM2fOlHR2mLe2tlYZGRkKBoORx0yaNElHjx6VJC1ZskRf+9rXBrzG+PHjNXbsWNXV1UmStm3bptOnT+vDDz8c8LgPP/xQubm5ys7OlnT2Ajh69Kja29uVk5Ojn/70p7r11lt15513qre395xY4z1fkubNm6fS0tK4f2ic5KY2lqSFCxfqvvvuU1ZW1oDb8/LydMcdd6impkYFBQV68MEHR9AqzjOhX6JVVlbqwQcfPKfdEz2fa/+skbax5J9rPx5T+uuee+7Rm2++qXnz5qm8vFwlJSUx4z127FgktuzsbOXm5ur48eOaPn26HnvsMV1wwQUjbZK0c1sbx/v9Mnr0aN18882qqqrSvffeq+XLl8f84OUFpvTZVVddpW3btkk6+4XTRx99FHPqF+8L69vYD+8LO/tEiv/3N971HM2uz0iOFQ45fPiw7rnnHpWWlmrq1KnKyMiI3BcOhwccD5aRkaHKyko988wzWrhwoTo7OzVu3DiNGjVqwONivU5GRoZ6e3vV1tamvLw8vfjii1q2bJmWL19+znniPd8t3NDGQ1mzZo0KCwslSbfddpv+93//V52dnSm9homc7JfoGD788EPdcMMNMc/DtW99Gw/Fq9d+PE731/e+9z3dfvvtqqur07/+67/qwQcfPGd9QSzhcFiZme6ov+XWNu63YsUKfeMb31BmZqYKCgo0duxYvffee0k/342c7rOKigq9+uqruvnmm/XGG2/oiiuuOOf5sfC+sL6N+3nxfWFHn6Qi1vVs12ek7LS/YhLq6+tVUlKiVatWKRQKac+ePQO+OWhtbdWkSZOGfI3s7Gxt3rxZktTe3q5/+qd/0rhx41RcXBx5zMsvv6zOzk719vYqKysr8rrjx49Xdna2brrpJknSF7/4RX3yySdqb2/XPffck/D5buCWNq6uro557r6+Pj3zzDPnfMsRb0TCLZzul347d+7UggULBrxuKs83mVva2G/Xfjwm9NeuXbu0Zs0aSdKsWbM0YcIENTQ06Omnn9axY8ckSc8++6wmTZqktrY2fepTn9KZM2d04sQJjRs3Lq3tYQU3tfHkyZNjnn/z5s266aabNH78eElnPyT1f4vtRSb02ZkzZ/TDH/5QOTk5On36tF588UVNmTJFS5cu5X3x/+xqY7+8L+zqk3h/fyXFvZ6d+Ixk+1cdR44c0fLly7Vu3TqFQiFJ0owZM/T+++/r97//vXp7e7V161Zdf/31Q77OqlWrtH//fknS888/r/nz5yszM1PV1dWRf6NGjdJ1112n7du3S5K2bNmi66+/Xjk5OfrCF74QGWJ+5513dN5552n8+PFJPd90bmrjeDIzM/XLX/5S//mf/xl53RkzZmjs2LEjbh+nmNAv/d555x1dd911A16Xa/9P7GjjeLx47cdjSn9dccUV2rlzp6Sz02yOHTumyy67TM8991zk+ZMnT1ZBQYG2bNkiSdq+fbuuu+66EX1Dawe3tXE8b7/9tl5++WVJZ6uf9vX16fLLLx9Z4xjKlD7bsGGDdu3aJensh9LPfe5zGj9+PO+LKHa1cTxeel/Y2SdDiXc9O/EZyfZ0e9OmTerp6VFFRUXktsWLF6uiokIrVqxQT0+PCgoKIgsp4/m7v/s7Pfroozp58qQ+85nP6LHHHov5uEcffVRlZWX60Y9+pIsuukjr16+XJD322GNavXq1fvrTnyo7O1sbNmyIOTwf7/kmc1sbx/PEE0/ou9/9rn74wx/qwgsvjJRjdStT+kWS/vCHPwz5iz/R803ltjaOx2vXfjym9FdFRYVWr16t5557Tjk5OXriiSeUl5d3zvMfeOABlZWVKRQKKS8vT+vWrRvBT28Pt7VxPI888ojKyspUXV2t0aNH6x//8R9dM6UuVab02d/+7d/qoYce0saNGzV58mQ9/vjjMZ/P+8L6No7HS+8Lu/sknmSvZzs+I2WEw+Fw2l8VAAAAADAs7ky3AQAAAMCjSNIAAAAAwCAkaQAAAABgEJI0AAAAADAISRoAAAAAGIQkDQAAAAAMQpIGAAAAAAYhSQMAAAAAg/wfNzlLNQlBu74AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 1080x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(15,6))\n",
    "mpf.candlestick_ochl(ax, df_arr, width=0.6, colorup='r', colordown='g', alpha=1.0)\n",
    "plt.grid(True)  # 绘制网格\n",
    "ax.xaxis_date()  # 设置x轴的刻度为日期"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**candlestick_ochl()函数的参数：**\n",
    "\n",
    "    ax：绘图Axes的实例，也就是画布中的子图；\n",
    "\n",
    "    df_arr：股价历史数据；\n",
    "\n",
    "    width：图像中红绿矩形的宽度；\n",
    "\n",
    "    colorup：收盘价格大于开盘价格时矩形的颜色；\n",
    "\n",
    "    colordown：收盘价格低于开盘价格时矩形的颜色；\n",
    "\n",
    "    alpha：矩形的颜色的透明度；"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "(6) 绘制K线图及均线图\n",
    "\n",
    "有了K线图之后，我们再来补上均线图，这里我们主要补上5日均线和10日均线图，首先我们通过如下代码构造5日均线和10日均线数据："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>date</th>\n",
       "      <th>open</th>\n",
       "      <th>close</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>volume</th>\n",
       "      <th>code</th>\n",
       "      <th>MA5</th>\n",
       "      <th>MA10</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>99</th>\n",
       "      <td>2019-06-03</td>\n",
       "      <td>26.81</td>\n",
       "      <td>26.44</td>\n",
       "      <td>27.02</td>\n",
       "      <td>26.28</td>\n",
       "      <td>317567.0</td>\n",
       "      <td>000002</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>100</th>\n",
       "      <td>2019-06-04</td>\n",
       "      <td>26.47</td>\n",
       "      <td>26.30</td>\n",
       "      <td>26.54</td>\n",
       "      <td>26.25</td>\n",
       "      <td>203260.0</td>\n",
       "      <td>000002</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101</th>\n",
       "      <td>2019-06-05</td>\n",
       "      <td>26.64</td>\n",
       "      <td>27.03</td>\n",
       "      <td>27.28</td>\n",
       "      <td>26.63</td>\n",
       "      <td>576164.0</td>\n",
       "      <td>000002</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>102</th>\n",
       "      <td>2019-06-06</td>\n",
       "      <td>27.01</td>\n",
       "      <td>27.12</td>\n",
       "      <td>27.29</td>\n",
       "      <td>26.92</td>\n",
       "      <td>333792.0</td>\n",
       "      <td>000002</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>103</th>\n",
       "      <td>2019-06-10</td>\n",
       "      <td>27.29</td>\n",
       "      <td>27.81</td>\n",
       "      <td>28.05</td>\n",
       "      <td>27.17</td>\n",
       "      <td>527547.0</td>\n",
       "      <td>000002</td>\n",
       "      <td>26.940</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>104</th>\n",
       "      <td>2019-06-11</td>\n",
       "      <td>27.87</td>\n",
       "      <td>28.33</td>\n",
       "      <td>28.45</td>\n",
       "      <td>27.85</td>\n",
       "      <td>449630.0</td>\n",
       "      <td>000002</td>\n",
       "      <td>27.318</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>105</th>\n",
       "      <td>2019-06-12</td>\n",
       "      <td>28.24</td>\n",
       "      <td>28.00</td>\n",
       "      <td>28.29</td>\n",
       "      <td>27.81</td>\n",
       "      <td>269372.0</td>\n",
       "      <td>000002</td>\n",
       "      <td>27.658</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>106</th>\n",
       "      <td>2019-06-13</td>\n",
       "      <td>28.00</td>\n",
       "      <td>27.83</td>\n",
       "      <td>28.05</td>\n",
       "      <td>27.58</td>\n",
       "      <td>250431.0</td>\n",
       "      <td>000002</td>\n",
       "      <td>27.818</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>107</th>\n",
       "      <td>2019-06-14</td>\n",
       "      <td>28.01</td>\n",
       "      <td>27.93</td>\n",
       "      <td>28.29</td>\n",
       "      <td>27.78</td>\n",
       "      <td>311417.0</td>\n",
       "      <td>000002</td>\n",
       "      <td>27.980</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>108</th>\n",
       "      <td>2019-06-17</td>\n",
       "      <td>27.80</td>\n",
       "      <td>27.91</td>\n",
       "      <td>28.20</td>\n",
       "      <td>27.75</td>\n",
       "      <td>171672.0</td>\n",
       "      <td>000002</td>\n",
       "      <td>28.000</td>\n",
       "      <td>27.470</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>109</th>\n",
       "      <td>2019-06-18</td>\n",
       "      <td>28.08</td>\n",
       "      <td>27.70</td>\n",
       "      <td>28.11</td>\n",
       "      <td>27.40</td>\n",
       "      <td>219162.0</td>\n",
       "      <td>000002</td>\n",
       "      <td>27.874</td>\n",
       "      <td>27.596</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110</th>\n",
       "      <td>2019-06-19</td>\n",
       "      <td>28.20</td>\n",
       "      <td>27.73</td>\n",
       "      <td>28.38</td>\n",
       "      <td>27.59</td>\n",
       "      <td>390157.0</td>\n",
       "      <td>000002</td>\n",
       "      <td>27.820</td>\n",
       "      <td>27.739</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>111</th>\n",
       "      <td>2019-06-20</td>\n",
       "      <td>27.70</td>\n",
       "      <td>28.45</td>\n",
       "      <td>28.45</td>\n",
       "      <td>27.63</td>\n",
       "      <td>577484.0</td>\n",
       "      <td>000002</td>\n",
       "      <td>27.944</td>\n",
       "      <td>27.881</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>112</th>\n",
       "      <td>2019-06-21</td>\n",
       "      <td>28.40</td>\n",
       "      <td>28.31</td>\n",
       "      <td>28.52</td>\n",
       "      <td>28.12</td>\n",
       "      <td>492537.0</td>\n",
       "      <td>000002</td>\n",
       "      <td>28.020</td>\n",
       "      <td>28.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>113</th>\n",
       "      <td>2019-06-24</td>\n",
       "      <td>28.12</td>\n",
       "      <td>28.13</td>\n",
       "      <td>28.25</td>\n",
       "      <td>28.03</td>\n",
       "      <td>270128.0</td>\n",
       "      <td>000002</td>\n",
       "      <td>28.064</td>\n",
       "      <td>28.032</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           date   open  close   high    low    volume    code     MA5    MA10\n",
       "99   2019-06-03  26.81  26.44  27.02  26.28  317567.0  000002     NaN     NaN\n",
       "100  2019-06-04  26.47  26.30  26.54  26.25  203260.0  000002     NaN     NaN\n",
       "101  2019-06-05  26.64  27.03  27.28  26.63  576164.0  000002     NaN     NaN\n",
       "102  2019-06-06  27.01  27.12  27.29  26.92  333792.0  000002     NaN     NaN\n",
       "103  2019-06-10  27.29  27.81  28.05  27.17  527547.0  000002  26.940     NaN\n",
       "104  2019-06-11  27.87  28.33  28.45  27.85  449630.0  000002  27.318     NaN\n",
       "105  2019-06-12  28.24  28.00  28.29  27.81  269372.0  000002  27.658     NaN\n",
       "106  2019-06-13  28.00  27.83  28.05  27.58  250431.0  000002  27.818     NaN\n",
       "107  2019-06-14  28.01  27.93  28.29  27.78  311417.0  000002  27.980     NaN\n",
       "108  2019-06-17  27.80  27.91  28.20  27.75  171672.0  000002  28.000  27.470\n",
       "109  2019-06-18  28.08  27.70  28.11  27.40  219162.0  000002  27.874  27.596\n",
       "110  2019-06-19  28.20  27.73  28.38  27.59  390157.0  000002  27.820  27.739\n",
       "111  2019-06-20  27.70  28.45  28.45  27.63  577484.0  000002  27.944  27.881\n",
       "112  2019-06-21  28.40  28.31  28.52  28.12  492537.0  000002  28.020  28.000\n",
       "113  2019-06-24  28.12  28.13  28.25  28.03  270128.0  000002  28.064  28.032"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['MA5'] = df['close'].rolling(5).mean()\n",
    "df['MA10'] = df['close'].rolling(10).mean()\n",
    "\n",
    "df.head(15)  # 查看此时的前15行"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 有了5日均线和10日均线数据后，就可以将其绘制在图形中了，代码如下：\n",
    "plt.rcParams['font.sans-serif'] = ['SimHei']  # 用来正常显示中文标签\n",
    "\n",
    "fig, ax = plt.subplots(figsize=(15,6))\n",
    "\n",
    "mpf.candlestick_ochl(ax, df_arr, width=0.6, colorup='r', colordown='g', alpha=1.0) \n",
    "plt.plot(df_arr[:,0], df['MA5'])  # 绘制5日均线\n",
    "plt.plot(df_arr[:,0], df['MA10'])  # 绘制10日均线\n",
    "\n",
    "plt.grid(True)  # 绘制网格\n",
    "\n",
    "plt.title('万科A')  # 设置标题\n",
    "plt.xlabel('日期')  # 设置X轴图例\n",
    "plt.ylabel('价格')  # 设置Y轴图例\n",
    "\n",
    "ax.xaxis_date () # 设置x轴的刻度为日期"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "(7) 绘制股票K线图、均线图、成交量柱状图\n",
    "\n",
    "在现实中，和股票K线图、均线图一同出现的还有每日成交量的的柱状图，我们利用2.3.2节绘制多图的知识点，即可通过如下代码在一张画布中绘制两个子图，包含K线图、均线图、成交量柱状图："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x576 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axes = plt.subplots(2, 1, sharex=True, figsize=(15,8))\n",
    "ax1, ax2 = axes.flatten()\n",
    "\n",
    "# 绘制第一张子图：K线图和均线图\n",
    "mpf.candlestick_ochl(ax1, df_arr, width=0.6, colorup = 'r', colordown = 'g', alpha=1.0)\n",
    "\n",
    "ax1.plot(df_arr[:,0], df['MA5'])  # 绘制5日均线\n",
    "ax1.plot(df_arr[:,0], df['MA10'])  # 绘制10日均线\n",
    "\n",
    "ax1.set_title('万科A')  # 设置子图标题\n",
    "ax1.set_ylabel('价格')  # 设置子图Y轴标签\n",
    "ax1.grid(True)\n",
    "ax1.xaxis_date()\n",
    "\n",
    "# 绘制第二张子图：成交量图\n",
    "ax2.bar(df_arr[:,0], df_arr[:,5])  # 绘制成交量柱状图\n",
    "ax2.set_xlabel('日期')  # 设置子图X轴标签\n",
    "ax2.set_ylabel('成交量')  # 设置子图Y轴标签\n",
    "ax2.grid(True)\n",
    "ax2.xaxis_date()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "其中第1-2行代码利用2.3.2节绘制多图相关知识点先构造一个画布和两个子图，这里同时设置sharex参数为True，这样两张子图就可以共用一个坐标轴了；第4-13行绘制第一张子图，其中在子图中设置标题或者坐标轴标题得使用set_title()、set_ylabel()、set_xlabel()这样的函数；第15-20行绘制第二张子图：成交量图，其中df_arr[:,0]表示二维数组的第1列，也即日期那列，df_arr[:,5]表示二维数组的第6列，也即成交量那列数据，然后通过2.3.1节讲过的bar()函数绘制成柱状图。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "我们可以和新浪财经网上的实际图像对比一下，如下图所示，发现通过Python绘制的K线图相关图片和网上的图片基本一致。\n",
    "![图片解释](https://uploader.shimo.im/f/BhOBA3Zs73Yy74lA.png!thumbnail)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "至此，数据分析的相关3大武器库已经给大家讲解完毕了，其实关于这三个库还有很多可以挖掘的知识点，由于篇幅有限，这里就不再赘述。这一章内容相对较多，读者朋友可以将这一章当作一个工具章，有需要的时候再返回看看需要用到的知识点。"
   ]
  }
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